Many modern forms of information sensing systems (particularly those in the "internal-imaging" sciences, such as computer-aided tomography (CAT) scanning and nuclear magnetic resonance (NMR or MRI) imaging, or the more "external-imaging" sciences, such as radar, sonar and the like) utilize beams of various energies to interrogate a sample and provide response information which is to be processed to form a user-viewable image in which specific objects are to be recognized. All of the response signals are obtained with an undesired noise contribution; there have been many and varied signal processing methods provided over the years for operating on the sensed data, so as to provide a display with the highest attainable signal-to-noise ratio. One method to realize this, as well as other, signal processing goals utilizes the Radon transform R(.rho.,.theta.), which is a projection of all line integrals (each at a different distance .rho. from an origin) orthogonal to the .rho. line and at an angle .theta. with respect to one of the axes of the signal data space; thus, as is known to the art EQU R(.rho.,.theta.)=.intg..intg.I(x,y).delta.(.rho.-x* cos .theta.-y* sin .theta.)dx dy,
where the inner integral lower and upper bounds are respectively x.sub.l and x.sub.u (the lower and upper sides of the data space) and the outer integral lower and upper bounds are respectively y.sub.l and y.sub.u (the bottom and top sides of the data space) and I(x,y) is the amplitude, or intensity, of the signal at pixel (x,y). A particularly useful Systolic Radon Transform Processor was described and claimed in my U.S. Pat. No. 4,930,076, issued May 29, 1990, assigned to the assignee of the present invention and incorporated herein in its entirety by reference.
In many systems, the response data is presented as a series of "snapshots" in a continuously-incremented data manifold, i.e. with each snapshot being one of a multiplicity of sequential line sets of data each taken at one of a series of sequential time intervals and arranged as a two-dimensional (data vs. time) space. The data can be placed in the manifold in either its original form or can be transformed first in accordance with some selected transformational process (e.g. by taking the frequency transform of the amplitudes, and the like). The transformed data set at any one time is set forth as a line parallel to one axis (say, the +D axis) and the various data/transform sets are sequentially provided perpendicular to the time (say, +T) axis, orthogonal to the data D axis, with a time interval .DELTA.T therebetween. I have found it advantageous to window the manifold and provide the Radon transform of the set of the data lines contained in that window for further processing for detection of coherent features. It is therefore highly desirable to provide a Radon video transform processor which will recursively process each entire window of data, as the window advances in time, in a manner which will properly account for the newest data line, provided at the latest time interval, while removing the oldest line of data from the present data window.